Solar/Wind Forecasting to Increase the Reliability of the RE System
Approach using Artificial Neural Networks based on Heuristic Algorithm
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Solar and wind energy are the most widely used renewable energy resources. Its availability varies from season to season, day to day, and even within a day itself. Due to this variability, forecasting large solar PV power and wind power plants becomes necessary. A reasonably reliable forecast is an important input to the state load dispatch centers for scheduling power generation by various sources of energy. Solar forecasting is used to minimize the uncertainty in a solar-based power generation system as solar energy is dependent on weather data (i.e. temperature and irradiance) as well as th...
Solar and wind energy are the most widely used renewable energy resources. Its availability varies from season to season, day to day, and even within a day itself. Due to this variability, forecasting large solar PV power and wind power plants becomes necessary. A reasonably reliable forecast is an important input to the state load dispatch centers for scheduling power generation by various sources of energy. Solar forecasting is used to minimize the uncertainty in a solar-based power generation system as solar energy is dependent on weather data (i.e. temperature and irradiance) as well as the day/night cycle. Wind forecasting of variable wind resources helps in generation scheduling and results in an increased and reliable generation.
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